code: def test_prepare_data_for_bayes_opt(parameters, results):
      X, y, y_var = GPyOpt._prepare_data_for_bayes_opt(
          parameters, results
      )
      assert numpy.array_equal(
          X,
          numpy.array(
              [
                  [0.1, -3.0, 1, 111],
                  [0.4, -5.0, 0, 222],
                  [0.33, -2.0, 2, 288],
              ]
          ),
      )
  
      assert numpy.array_equal(y, numpy.array([[0.1], [0.055], [0.15]]))
  
imports: import sherpa
  import pandas
  import pytest
  import numpy
  import collections
  import GPyOpt
  from sherpa.algorithms.bayesian_optimization import GPyOpt
  from sherpa.algorithms import Repeat
label_desc: Use image node_id 12 for calling a global function with example usage: test_prepare_data_for_bayes_opt(parameters, results) without return types